Bayesian model reveals latent atrophy factors with dissociable cognitive trajectories in Alzheimer's disease

Proceedings of the National Academy of Sciences of the United States of America

Volumn 113, Issue 42, 2016, Pages E6535-E6544

  Zhang, Xiuming ^a   Mormino, Elizabeth C ^b   Sun, Nanbo ^a   Sperling, Reisa A ^b   Sabuncu, Mert R ^b,c   Yeo, B T Thomas ^a,b  

^a NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

^b MASSACHUSETTS GENERAL HOSPITAL   (United States)

^c MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

Alzheimer's disease heterogeneity; Alzheimer's disease subtypes; Mental disorder subtypes; Unsupervised machine learning; Voxel based morphometry

Indexed keywords

ALZHEIMER DISEASE; AMYGDALA; ARTICLE; BAYES THEOREM; BRAIN ATROPHY; CEREBELLUM; COGNITION; CORPUS STRIATUM; EXECUTIVE FUNCTION; FRONTAL CORTEX; HIPPOCAMPUS; HUMAN; MEMORY; MILD COGNITIVE IMPAIRMENT; NUCLEAR MAGNETIC RESONANCE IMAGING; OCCIPITAL CORTEX; PARIETAL CORTEX; PRIORITY JOURNAL; TEMPORAL CORTEX; THALAMUS; VOXEL BASED MORPHOMETRY; ATROPHY; BRAIN; COGNITIVE DEFECT; DEMENTIA; DIAGNOSTIC IMAGING; FEMALE; MALE; PATHOLOGY; PATHOPHYSIOLOGY; PSYCHOLOGY; RISK FACTOR;

ALZHEIMER DISEASE; ATROPHY; BAYES THEOREM; BRAIN; COGNITIVE DYSFUNCTION; DEMENTIA; FEMALE; HUMANS; MAGNETIC RESONANCE IMAGING; MALE; RISK FACTORS;

EID: 84991583783     PISSN: 00278424     EISSN: 10916490     Source Type: Journal    
DOI: 10.1073/pnas.1611073113     Document Type: Article

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